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Journal articles on the topic 'Metagenesis'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

Sampei, Yoshikazu, Tetsuya Shiomi, and Hiroto Ohira. "Isomerization of methylphenanthrenes during catagenesis and metagenesis." Journal of the Japanese Association for Petroleum Technology 69, no. 2 (2004): 190–99. http://dx.doi.org/10.3720/japt.69.190.

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2

SCHIERWATER, BERND, and HEIKE HADRYS. "Environmental factors and metagenesis in the hydroidEleutheria dichotoma." Invertebrate Reproduction & Development 34, no. 2-3 (1998): 139–48. http://dx.doi.org/10.1080/07924259.1998.9652646.

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3

Sustavov, O. A. "Dynamic recrystallization of quartz in veins in sandstones of metagenesis zone (Kular district, Yakutia)." Proceedings of higher educational establishments. Geology and Exploration, no. 6 (January 3, 2019): 33–40. http://dx.doi.org/10.32454/0016-7762-2018-6-33-40.

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Bulging recrystallization (BR) has been considered in the deformed quartz veins in the lower Triassic sandstones of the metagenesis zone in the North-Western part of the Kular district, Yakutia. BR is characterized by the formation of sutured boundaries of individuals during the crystalloplastic deformation of quarz. To these boundaries, the recrystallization grains are confined, the size of which (in this case, 0,01—0,02 mm) corresponds to the size of the teeth at the boundaries of individuals. Such fine recrystallization grains can fix with their formation the peak crustal stresses arising u

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4

Jolley, Keith A., Rupert J. M. Russell, David W. Hough, and Michael J. Danson. "Site-Directed Metagenesis and Halophilicity of Dihydrolipoamide Dehydrogenase from the Halophilic Archaeon, Haloferax Volcanii." European Journal of Biochemistry 248, no. 2 (1997): 362–68. http://dx.doi.org/10.1111/j.1432-1033.1997.00362.x.

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5

Raksabrata, M. R., A. Rahmat, and S. Diana. "The relation of student’s diagram comprehension, knowledge and cognitive activities while studying mosses metagenesis diagram." Journal of Physics: Conference Series 1157 (February 2019): 022105. http://dx.doi.org/10.1088/1742-6596/1157/2/022105.

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6

Nisa, Khairun, Aulia Ajizah, and Sri Amintarti. "The Validity of Learning Media in the Form of Booklet Types of Pteridophyta (Fern) in the Riverbanks of Wisata Alam Sungai Kembang for Senior High School Grade X." BIO-INOVED : Jurnal Biologi-Inovasi Pendidikan 3, no. 2 (2021): 92. http://dx.doi.org/10.20527/bino.v3i2.9978.

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Pteridophyta is a sub-concept on Plant (Plantae) material in the Biology subject for Grade X Senior High School. In this competency, students are expected to apply classification principles to classify plants into divisions based on observations of plant morphology and metagenesis and linking their role in the continuity of life on earth. However, most students still find it difficult to understand the concept. This Pteridophyta is due to the lack of local potential-based references that are directly related to student life, one of which is learning media. Learning media is one of the means to

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7

Aryanto, Rofi Surya. "MINYAK ATSIRI KULIT KAYU MANIS (Cinnamomun Burmanni) SEBAGAI PENGHAMBAT PERTUMBUHAN LUMUT PADA CANDI KEDATON." Siddhayatra: Jurnal Arkeologi 25, no. 1 (2020): 47–58. http://dx.doi.org/10.24832/siddhayatra.v25i1.177.

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Candi Kedaton yang masuk dalam Kawasan Percandian Muaro Jambi, terletak di kecamatan Maro Sebo, Kabupaten Muaro Jambi. Candi Kedaton sampai sekarang masih dalam tahap pemugaran bagian halaman II, namun perlu evaluasi pasca pemugaran untuk pelestarian. Kerusakan pelapukan pada bata Candi Kedaton salah satunya disebabkan faktor eksternal yaitu lumut. Minyak atsiri kulit kayu manis bisa difungsikan sebagai penghambat pertumbuhan lumut pada Candi Kedaton, khususnya pada bata lepas. Medote penelitian bersifat kuantitafif, tahapannya meliputi pengumpulan data, pengolahan data, analisis data, sintesi

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8

Bentlage, Bastian, Karen J. Osborn, Dhugal J. Lindsay, Russell R. Hopcroft, Kevin A. Raskoff, and Allen G. Collins. "Loss of metagenesis and evolution of a parasitic life style in a group of open-ocean jellyfish." Molecular Phylogenetics and Evolution 124 (July 2018): 50–59. http://dx.doi.org/10.1016/j.ympev.2018.02.030.

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9

Jin, Xiao, Jia Wu, Peng Fang, Zhihuan Zhang, Meijun Li, and Ningning Zhong. "Kinetics and fate of organosulphur compounds during the metagenesis stage of thermal maturation: Hydrous pyrolysis investigations on dibenzothiophene." Marine and Petroleum Geology 130 (August 2021): 105129. http://dx.doi.org/10.1016/j.marpetgeo.2021.105129.

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10

Lehmann, A. R. "Use of recombinant DNA techniques in cloning DNA repair genes and in the study of metagenesis in mammalian cells." Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis 150, no. 1-2 (1985): 61–67. http://dx.doi.org/10.1016/0027-5107(85)90101-0.

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11

Barberes, Gabriel A., Rui Pena dos Reis, Nuno L. Pimentel, et al. "Geochemical Considerations from the Carboniferous Unconventional Petroleum System of SW Iberia." Minerals 11, no. 8 (2021): 811. http://dx.doi.org/10.3390/min11080811.

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The Baixo Alentejo Flysch Group (BAFG) is an important stratigraphic unit that covers over half of the South Portuguese Zone (SPZ) depositional area, and it is composed by three main tectono-stratigraphic units: the Mértola, Mira, and Brejeira formations. All of these formations contain significant thicknesses of black shales and have several wide areas with 0.81 wt.%, 0.91 wt.%, and 0.72 wt.% average total organic carbon (TOC) (respectively) and thermal maturation values within gas zones (overmature). This paper is considering new data from classical methods of organic geochemistry characteri

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12

DELHALLE, L., N. KORSAK, B. TAMINIAU, et al. "Exploring the Bacterial Diversity of Belgian Steak Tartare Using Metagenetics and Quantitative Real-Time PCR Analysis." Journal of Food Protection 79, no. 2 (2016): 220–29. http://dx.doi.org/10.4315/0362-028x.jfp-15-185.

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ABSTRACT Steak tartare is a popular meat dish in Belgium. It is prepared with raw minced beef and is eaten with sauce, vegetables, and spices. Because it contains raw meat, steak tartare is highly prone to bacterial spoilage. The objective of this study was to explore the diversity of bacterial flora in steak tartare in Belgium according to the source and to determine which bacteria are able to grow during shelf life. A total of 58 samples from butchers' shops, restaurants, sandwich shops, and supermarkets were collected. These samples were analyzed using 16S rDNA metagenetics, a classical mic

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13

Miranda, Yula. "Inovasi Pembelajaran Biologi Materi Morfologi Tumbuhan Berbasis Etnobiologi Bagi Peserta Didik." Wahana-Bio: Jurnal Biologi dan Pembelajarannya 12, no. 1 (2020): 21. http://dx.doi.org/10.20527/wb.v12i1.9557.

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Inovasi pembelajaran penting untuk dilakukan agar peserta didik senang belajar dan mudah memahami apa yang dipelajari. Sumber belajar peserta didik berbagai macam, tidak terbatas hanya dari pengajar, tetapi tersedia di sekitar peserta didik dimanapun mereka berada. Salah satu sumber belajar yang ada di sekitar sekolah peserta didik adalah tumbuh-tumbuhan. Tumbuh-tumbuhan memiliki manfaat yang beranekaragam dan sangat penting bagi masyarakat, sebab itu peserta didik penting mengetahui dan memahami karakteristik tumbuhan. Pengenalan karakteristik tumbuhan dapat dilakukan dengan menerapkan prinsi

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14

Bentlage, Bastian, Karen J. Osborn, Dhugal J. Lindsay, Russell R. Hopcroft, Kevin A. Raskoff, and Allen G. Collins. "Corrigendum to "Loss of metagenesis and evolution of a parasitic life style in a group of open-ocean jellyfish" [Molecular Phylogenetics and Evolution 124 (2018) 50-59]." Molecular Phylogenetics and Evolution 126 (September 2018): 390–91. http://dx.doi.org/10.1016/j.ympev.2018.06.017.

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15

Frigyesi, Attila, and Mattias Höglund. "Non-Negative Matrix Factorization for the Analysis of Complex Gene Expression Data: Identification of Clinically Relevant Tumor Subtypes." Cancer Informatics 6 (January 2008): CIN.S606. http://dx.doi.org/10.4137/cin.s606.

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Non-negative matrix factorization (NMF) is a relatively new approach to analyze gene expression data that models data by additive combinations of non-negative basis vectors (metagenes). The non-negativity constraint makes sense biologically as genes may either be expressed or not, but never show negative expression. We applied NMF to five different microarray data sets. We estimated the appropriate number metagens by comparing the residual error of NMF reconstruction of data to that of NMF reconstruction of permutated data, thus finding when a given solution contained more information than noi

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16

Bedognetti, Davide, Ena Wang, and Francesco M. Marincola. "Meta-analysis and metagenes." OncoImmunology 3, no. 4 (2014): e28727. http://dx.doi.org/10.4161/onci.28727.

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17

BOSIO, MATTIA, PAU BELLOT, PHILIPPE SALEMBIER, and ALBERT OLIVERAS-VERGÉS. "GENE EXPRESSION DATA CLASSIFICATION COMBINING HIERARCHICAL REPRESENTATION AND EFFICIENT FEATURE SELECTION." Journal of Biological Systems 20, no. 04 (2012): 349–75. http://dx.doi.org/10.1142/s0218339012400025.

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A general framework for microarray data classification is proposed in this paper. It produces precise and reliable classifiers through a two-step approach. At first, the original feature set is enhanced by a new set of features called metagenes. These new features are obtained through a hierarchical clustering process on the original data. Two different metagene generation rules have been analyzed, called Treelets clustering and Euclidean clustering. Metagenes creation is attractive for several reasons: first, they can improve the classification since they broaden the available feature space a

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18

Handelsman, Jo. "Metagenetics: spending our inheritance on the future." Microbial Biotechnology 2, no. 2 (2009): 138–39. http://dx.doi.org/10.1111/j.1751-7915.2009.00090_8.x.

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19

Hirai, Junya, Satoshi Nagai, and Kiyotaka Hidaka. "Evaluation of metagenetic community analysis of planktonic copepods using Illumina MiSeq: Comparisons with morphological classification and metagenetic analysis using Roche 454." PLOS ONE 12, no. 7 (2017): e0181452. http://dx.doi.org/10.1371/journal.pone.0181452.

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20

Brunet, J. P., P. Tamayo, T. R. Golub, and J. P. Mesirov. "Metagenes and molecular pattern discovery using matrix factorization." Proceedings of the National Academy of Sciences 101, no. 12 (2004): 4164–69. http://dx.doi.org/10.1073/pnas.0308531101.

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21

Cheng, Wei-Yi, Tai-Hsien Ou Yang, and Dimitris Anastassiou. "Biomolecular Events in Cancer Revealed by Attractor Metagenes." PLoS Computational Biology 9, no. 2 (2013): e1002920. http://dx.doi.org/10.1371/journal.pcbi.1002920.

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22

Wong, Chung-Shun, Tzu-Ting Chen, Wei-Pin Chang, et al. "Prognostic Effect of Comorbid Disease and Immune Gene Expression on Mortality in Kidney Cancer—A Population Based Study." Cancers 12, no. 6 (2020): 1654. http://dx.doi.org/10.3390/cancers12061654.

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The effect of comorbidities and the immune profiles of the kidney cancer microenvironment play a major role in patients’ prognosis and survival. Using the National Health Insurance Research Database (Taiwan), we identified patients aged >20 years with a first diagnosis of kidney cancer between 2005 and 2014. Differences in demographic characteristics and comorbidities were examined using the Pearson chi-squared test or the t test. The Cox regression model was used to construct the nomogram. RNA-seq data were applied from The Cancer Genome Atlas database, and correlations between immune meta

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23

Basgier, Christopher. "Extra-Disciplinary Writing in the Disciplines: Towards a Metageneric Pedagogy." Across the Disciplines 11, no. 2 (2014): 1–19. http://dx.doi.org/10.37514/atd-j.2014.11.2.04.

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24

Davicioni, Elai, James R. Anderson, Jonathan D. Buckley, William H. Meyer, and Timothy J. Triche. "Gene Expression Profiling for Survival Prediction in Pediatric Rhabdomyosarcomas: A Report From the Children's Oncology Group." Journal of Clinical Oncology 28, no. 7 (2010): 1240–46. http://dx.doi.org/10.1200/jco.2008.21.1268.

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Purpose We investigated whether tumors from diagnostic biopsies of primary rhabdomyosarcoma (RMS) contain relevant prognostic information in the form of gene expression signatures that can be used to model and predict outcome of patients. Patients and Methods A 22,000-probe set microarray was used to evaluate 120 RMS specimens and correlate gene expression patterns to survival. Multivariate gene expression models or metagenes were developed using cross-validated Cox regression proportional hazards modeling and were evaluated using Kaplan-Meier analysis. Results A 34-metagene, based on expressi

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Jin, Xing, Weihua Wang, Fang Liu, and Zengping Chen. "Metagenes-Based Kernel Sparse Representation for Classification of Tumors." Journal of Computational and Theoretical Nanoscience 12, no. 10 (2015): 3357–62. http://dx.doi.org/10.1166/jctn.2015.4125.

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26

Bianchini, Giampaolo, Yuan Qi, Ricardo H. Alvarez, et al. "Molecular Anatomy of Breast Cancer Stroma and Its Prognostic Value in Estrogen Receptor–Positive and –Negative Cancers." Journal of Clinical Oncology 28, no. 28 (2010): 4316–23. http://dx.doi.org/10.1200/jco.2009.27.2419.

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Purpose The purpose of this study was to identify genes enriched in breast cancer stroma, assess the stromal gene expression differences between estrogen receptor (ER) –positive and –negative cancers, and separately determine their prognostic value in these two subtypes of breast cancers. Methods We compared gene expression profiles of pairs of fine-needle (stroma-poor) and core-needle (stroma-rich) biopsies from 37 cancers to identify stroma-associated genes. We defined stromal metagenes and tested their prognostic values in 684 node-negative patients who received no systemic adjuvant therapy

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27

Çakır, M. Volkan, Hans Binder, and Henry Wirth. "Profiling of Genetic Switches using Boolean Implications in Expression Data." Journal of Integrative Bioinformatics 11, no. 1 (2014): 30–54. http://dx.doi.org/10.1515/jib-2014-246.

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Summary Correlation analysis assuming coexpression of the genes is a widely used method for gene expression analysis in molecular biology. Yet growing extent, quality and dimensionality of the molecular biological data permits emerging, more sophisticated approaches like Boolean implications. We present an approach which is a combination of the SOM (self organizing maps) machine learning method and Boolean implication analysis to identify relations between genes, metagenes and similarly behaving metagene groups (spots). Our method provides a way to assign Boolean states to genes/metagenes/spot

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28

Carugati, Laura, Cinzia Corinaldesi, Antonio Dell'Anno, and Roberto Danovaro. "Metagenetic tools for the census of marine meiofaunal biodiversity: An overview." Marine Genomics 24 (December 2015): 11–20. http://dx.doi.org/10.1016/j.margen.2015.04.010.

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Hirai, J., M. Kuriyama, T. Ichikawa, K. Hidaka, and A. Tsuda. "A metagenetic approach for revealing community structure of marine planktonic copepods." Molecular Ecology Resources 15, no. 1 (2014): 68–80. http://dx.doi.org/10.1111/1755-0998.12294.

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Heil, B. A., S. K. Thompson, T. A. Kearns, G. M. Davolli, G. King, and J. L. Sones. "Metagenetic Characterization of the Resident Equine Uterine Microbiome Using Multiple Techniques." Journal of Equine Veterinary Science 66 (July 2018): 111. http://dx.doi.org/10.1016/j.jevs.2018.05.156.

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31

Iwanowicz, Deborah D., Judy Y. Wu-Smart, Tugce Olgun, et al. "An updated genetic marker for detection of Lake Sinai Virus and metagenetic applications." PeerJ 8 (July 17, 2020): e9424. http://dx.doi.org/10.7717/peerj.9424.

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Background Lake Sinai Viruses (LSV) are common RNA viruses of honey bees (Apis mellifera) that frequently reach high abundance but are not linked to overt disease. LSVs are genetically heterogeneous and collectively widespread, but despite frequent detection in surveys, the ecological and geographic factors structuring their distribution in A. mellifera are not understood. Even less is known about their distribution in other species. Better understanding of LSV prevalence and ecology have been hampered by high sequence diversity within the LSV clade. Methods Here we report a new polymerase cha

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Urgard, Egon, Tõnu Vooder, Urmo Võsa, et al. "Metagenes Associated with Survival in Non-Small Cell Lung Cancer." Cancer Informatics 10 (January 2011): CIN.S7135. http://dx.doi.org/10.4137/cin.s7135.

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NSCLC (non-small cell lung cancer) comprises about 80% of all lung cancer cases worldwide. Surgery is most effective treatment for patients with early-stage disease. However, 30%–55% of these patients develop recurrence within 5 years. Therefore, markers that can be used to accurately classify early-stage NSCLC patients into different prognostic groups may be helpful in selecting patients who should receive specific therapies. A previously published dataset was used to evaluate gene expression profiles of different NSCLC subtypes. A moderated two-sample t-test was used to identify differential

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Jedrzejowicz, Joanna, and Piotr Jedrzejowicz. "Incremental Gene Expression Programming Classifier with Metagenes and Data Reduction." Complexity 2018 (November 7, 2018): 1–12. http://dx.doi.org/10.1155/2018/6794067.

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The paper proposes an incremental Gene Expression Programming classifier. Its main features include using two-level ensemble consisting of base classifiers in form of genes and the upper-level classifier in the form of metagene. The approach enables us to deal with big datasets through controlling computation time using data reduction mechanisms. The user can control the number of attributes used to induce base classifiers as well as the number of base classifiers used to induce metagenes. To optimize the parameter setting phase, an approach based on the Orthogonal Experiment Design principles

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Marchan, R., and H. M. Bolt. "Progress in gene expression profiling by the introduction of metagenes." Archives of Toxicology 86, no. 8 (2012): 1165–66. http://dx.doi.org/10.1007/s00204-012-0879-2.

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35

Mahlstedt, Nicolaj, and Brian Horsfield. "Metagenetic methane generation in gas shales I. Screening protocols using immature samples." Marine and Petroleum Geology 31, no. 1 (2012): 27–42. http://dx.doi.org/10.1016/j.marpetgeo.2011.06.011.

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36

Fonseca, Vera G., Gary R. Carvalho, Ben Nichols, et al. "Metagenetic analysis of patterns of distribution and diversity of marine meiobenthic eukaryotes." Global Ecology and Biogeography 23, no. 11 (2014): 1293–302. http://dx.doi.org/10.1111/geb.12223.

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37

da Silveira, Fábio Lang, and André Carrara Morandini. "Nausithoe aurea n. sp. (Scyphozoa: Coronatae: Nausithoidae), a species with two pathways of reproduction after strobilation: sexual and asexual." Bijdragen tot de Dierkunde 66, no. 4 (1997): 235–46. http://dx.doi.org/10.1163/26660644-06604004.

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Nausithoe aurea, a new species of scyphozoan Coronatae, is described from São Paulo State, Brazil. The solitary scyphistomae, with some zooxanthellae, strobilated producing planuloids and medusae; this represents an intermediate life cycle between that of metagenetic Nausithoidae and the submarine cave-dwelling, reduced medusa stage of Nausithoe planulophora (Werner, 1971). The periderm tube of the scyphistomae has 16 internal cusps in all whorls. The medusae present yellow pigment spots in most of their lappets. The early embryonic development is briefly described. Planuloid formation is hypo

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Bianchini, Giampaolo, Vera Cappelletti, Maurizio Callari, et al. "Proliferation-, estrogen-, and T-cell-related metagenes to predict outcome after adjuvant/neoadjuvant chemotherapy for operable breast cancer in the ECTO trial." Journal of Clinical Oncology 31, no. 15_suppl (2013): 1014. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.1014.

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1014 Background: Predicting recurrence in operable breast cancer (BC) despite optimal chemotherapy would be relevant to new drug development and tailored treatments. Methods: A large series (n=3,154) of public Affymetrix gene-expression profiles (GEP) was used to define prognostic/predictive metagenes in different BC subtypes. In ER+/HER2- a proliferation and an ER-related metagene were combined to predict low, intermediate and high risk of recurrence. In TN and in HER2+ a T cell metagene was used to predict low, intermediate and high risk (higher expression associated with lower risk). The me

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Molik, David C., DeAndre Tomlinson, Shane Davitt, et al. "Combining natural language processing and metabarcoding to reveal pathogen-environment associations." PLOS Neglected Tropical Diseases 15, no. 4 (2021): e0008755. http://dx.doi.org/10.1371/journal.pntd.0008755.

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Cryptococcus neoformans is responsible for life-threatening infections that primarily affect immunocompromised individuals and has an estimated worldwide burden of 220,000 new cases each year—with 180,000 resulting deaths—mostly in sub-Saharan Africa. Surprisingly, little is known about the ecological niches occupied by C. neoformans in nature. To expand our understanding of the distribution and ecological associations of this pathogen we implement a Natural Language Processing approach to better describe the niche of C. neoformans. We use a Latent Dirichlet Allocation model to de novo topic m

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Hirai, J., and A. Tsuda. "Metagenetic community analysis of epipelagic planktonic copepods in the tropical and subtropical Pacific." Marine Ecology Progress Series 534 (August 27, 2015): 65–78. http://dx.doi.org/10.3354/meps11404.

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Molik, David C., Michael E. Pfrender, and Scott J. Emrich. "Uncovering Effects from the Structure of Metabarcode Sequences for Metagenetic and Microbiome Analysis." Methods and Protocols 3, no. 1 (2020): 22. http://dx.doi.org/10.3390/mps3010022.

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The advent of next-generation sequencing has allowed for higher-throughput determination of which species live within a specific location. Here we establish that three analysis methods for estimating diversity within samples—namely, Operational Taxonomic Units; the newer Amplicon Sequence Variants; and a method commonly found in sequence analysis, minhash—are affected by various properties of these sequence data. Using simulations we show that the presence of Single Nucleotide Polymorphisms and the depth of coverage from each species affect the correlations between these approaches. Through th

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Zacharis, Z. N., and T. Panayiotopoulos. "A metagenetic algorithm for information filtering and collection from the World Wide Web." Expert Systems 18, no. 2 (2001): 99–108. http://dx.doi.org/10.1111/1468-0394.00161.

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Ou Yang, Tai-Hsien, Wei-Yi Cheng, Tian Zheng, Matthew A. Maurer, and Dimitris Anastassiou. "Breast Cancer Prognostic Biomarker Using Attractor Metagenes and the FGD3–SUSD3 Metagene." Cancer Epidemiology Biomarkers & Prevention 23, no. 12 (2014): 2850–56. http://dx.doi.org/10.1158/1055-9965.epi-14-0399.

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Fonseca, V. G., B. Nichols, D. Lallias, et al. "Sample richness and genetic diversity as drivers of chimera formation in nSSU metagenetic analyses." Nucleic Acids Research 40, no. 9 (2012): e66-e66. http://dx.doi.org/10.1093/nar/gks002.

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Ferrara, Massimo, Angelo Sisto, Giuseppina Mulè, Paola Lavermicocca, and Palmira De Bellis. "Metagenetic Analysis for Microbial Characterization of Focaccia Doughs Obtained by Using Two Different Starters: Traditional Baker’s Yeast and a Selected Leuconostoc citreum Strain." Foods 10, no. 6 (2021): 1189. http://dx.doi.org/10.3390/foods10061189.

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Lactic acid bacteria (LAB) decisively influence the technological, nutritional, organoleptic and preservation properties of bakery products. Therefore, their use has long been considered an excellent strategy to improve the characteristics of those goods. The aim of this study was the evaluation of microbial diversity in different doughs used for the production of a typical Apulian flatbread, named focaccia. Leavening of the analyzed doughs was obtained with baker’s yeast or by applying an innovative “yeast-free” protocol based on a liquid sourdough obtained by using Leuconostoc citreum strain

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Li, Qiyuan, Aron C. Eklund, Nicolai J. Birkbak, et al. "Consistent metagenes from cancer expression profiles yield agent specific predictors of chemotherapy response." BMC Bioinformatics 12, no. 1 (2011): 310. http://dx.doi.org/10.1186/1471-2105-12-310.

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RIGAKIS, N., N. ROUSSOS, E. KAMBERIS, and P. PROEDROU. "Hydrocarbon gas accumulations in Greece and their origin." Bulletin of the Geological Society of Greece 34, no. 3 (2001): 1265. http://dx.doi.org/10.12681/bgsg.17203.

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In the sedimentary basins of Greece are found a lot of hydrocarbon gases that can be distinguished in four categories. Surface gas seeps, gas shows in shallow water-wells, gases in exploration wells and hydrocarbon gas fields. The main gas shows are mainly located inside recent clastic sediments. Hydrocarbon amount varies between a few ppm and several units percent. Gases are classified in the biogenic gases of Katakolo onshore gas-field, the most surface gas seeps and the gases at shallow depths of exploration wells. Catagenetic are the gases of Katakolo oil field, the Epanomi and South Kaval

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Rodríguez-López, Pedro, Marta Bernárdez, Juan J. Rodríguez-Herrera, Ángel S. Comesaña, and Marta L. Cabo. "Identification and metagenetic characterisation of Listeria monocytogenes-harbouring communities present in food-related industrial environments." Food Control 95 (January 2019): 6–17. http://dx.doi.org/10.1016/j.foodcont.2018.07.023.

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Schmidt, M., B. Daniel, A. Lebrecht, H. Koelbl, J. G. Hengstler, and M. Gehrmann. "Characterization of triple-negative breast cancer utilizing microarray-based gene-expression profiling." Journal of Clinical Oncology 27, no. 15_suppl (2009): e22014-e22014. http://dx.doi.org/10.1200/jco.2009.27.15_suppl.e22014.

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e22014 Background: Triple-negative breast cancer (TNBC) is characterized by lack of expression of estrogen receptor (ER), progesterone receptor (PR) and HER-2. This makes it one of the most challenging subgroups for clinical decision-making. Methods: We analyzed gene-expression profiles of 200 node-negative breast cancer patients utilizing the Affymetrix HG-U133A array. After performing an unsupervised hierarchical cluster analysis using 2579 genes selected for variable expression within our dataset, we constructed metagenes for five dominant cluster (basal-like, luminal, proliferation, T-cell

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Bacci, G., M. Bazzicalupo, A. Benedetti, and A. Mengoni. "StreamingTrim 1.0: a Java software for dynamic trimming of 16S rRNA sequence data from metagenetic studies." Molecular Ecology Resources 14, no. 2 (2013): 426–34. http://dx.doi.org/10.1111/1755-0998.12187.

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